Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii Direct calls to spm_defauts are deprecated. Please use spm('Defaults',modality) or spm_get_defaults instead. loading mask. mapping volumes. checking that dimensions and voxel sizes of volumes are the same. Pre-allocating data array. Needed: 19568052 bytes Loading image number: 49 Elapsed time is 1.457698 seconds. Image names entered, but fullpath attribute is empty. Getting path info. Number of unique values in dataset: 4743442 Bit rate: 22.18 bits

SPM12: spm_check_registration (v7759) 12:31:50 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 Grouping contiguous voxels: 1 regions

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 8 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 28.57% Expected 2.45 outside 95% ellipsoid, found 8 Potential outliers based on mahalanobis distance: Bonferroni corrected: 5 images Cases 15 22 31 33 37 Uncorrected: 8 images Cases 1 12 15 22 31 33 37 43 Retained 15 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 44.90% Expected 2.45 outside 95% ellipsoid, found 3 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 3 images Cases 20 27 33 Mahalanobis (cov and corr, q<0.05 corrected): 5 images Outlier_count Percentage _____________ __________ global_mean 0 0 global_mean_to_variance 1 2.0408 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 2 4.0816 mahal_cov_uncor 8 16.327 mahal_cov_corrected 5 10.204 mahal_corr_uncor 3 6.1224 mahal_corr_corrected 0 0 Overall_uncorrected 10 20.408 Overall_corrected 5 10.204

SPM12: spm_check_registration (v7759) 12:32:07 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 Grouping contiguous voxels: 1 regions Grouping contiguous voxels: 1 regions Grouping contiguous voxels: 1 regions

current length is 49

after removing 5 participants, size is now 44

"participants that are outliers:... sub-…" "participants that are outliers:... sub-…" "participants that are outliers:... sub-…" "participants that are outliers:... sub-…" "participants that are outliers:... sub-…"

{'sub-0057'} {'sub-0074'} {'sub-0093'} {'sub-0098'} {'sub-0106'}

One-sample t-test Calculating t-statistics and p-values

SPM12: spm_check_registration (v7759) 12:32:11 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Image 1 FDR q < 0.050 threshold is 0.031651 Image 1 34 contig. clusters, sizes 1 to 62516 Positive effect: 62530 voxels, min p-value: 0.00000000 Negative effect: 667 voxels, min p-value: 0.00000191

SPM12: spm_check_registration (v7759) 12:32:12 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Image 1 FDR q < 0.001 threshold is 0.000261 Image 1 54 contig. clusters, sizes 1 to 25473 Positive effect: 26071 voxels, min p-value: 0.00000000 Negative effect: 21 voxels, min p-value: 0.00000191

SPM12: spm_check_registration (v7759) 12:32:13 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Setting up fmridisplay objects sagittal montage: 716 voxels displayed, 25376 not displayed on these slices sagittal montage: 873 voxels displayed, 25219 not displayed on these slices sagittal montage: 697 voxels displayed, 25395 not displayed on these slices axial montage: 4047 voxels displayed, 22045 not displayed on these slices axial montage: 4321 voxels displayed, 21771 not displayed on these slices

Input image 1 fullpath_was_empty _____________________________________________________________________ testr_low words_low testr_high words_high _________ ______________ __________ _________________ -0.13973 {'depression'} 0.25281 {'motor' } -0.13392 {'trait' } 0.24359 {'movements' } -0.13375 {'disorder' } 0.22494 {'sensorimotor' } -0.12855 {'work' } 0.2004 {'finger' } -0.12724 {'judgment' } 0.19791 {'somatosensory'} -0.12319 {'pair' } 0.19702 {'hand' } -0.11485 {'memory' } 0.19668 {'production' } -0.11404 {'face' } 0.19163 {'muscle' } -0.11253 {'decision' } 0.1835 {'sensory' } -0.1101 {'working' } 0.1762 {'execution' }

Loaded images: /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Pain.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Pain.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Pain.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Pain.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Pain.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Pain.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Pain.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Cognitive_Control.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Cognitive_Control.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Cognitive_Control.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Cognitive_Control.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Cognitive_Control.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Cognitive_Control.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Cognitive_Control.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Negative_Emotion.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Negative_Emotion.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Negative_Emotion.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Negative_Emotion.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Negative_Emotion.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Negative_Emotion.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Negative_Emotion.nii.gz /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Negative_Emotion.nii

Table of correlations Group:1 -------------------------------------- T-test on Fisher's r to Z transformed point-biserial correlations R_avg T P sig Pain Wholebrain 0.0031 0.4070 0.6858 0.0000 Cog Wholebrain 0.0133 2.3489 0.0230 1.0000 Emo Wholebrain -0.0148 -2.1761 0.0345 1.0000

Col 1: Pain Wholebrain Col 2: Cog Wholebrain Col 3: Emo Wholebrain --------------------------------------------- Tests of column means against zero --------------------------------------------- Name Mean_Value Std_Error T P Cohens_d ___________________ __________ _________ _______ ________ ________ {'Pain Wholebrain'} 0.0030508 0.0075832 0.40231 0.68924 0.057474 {'Cog Wholebrain' } 0.013274 0.0056524 2.3484 0.023022 0.33548 {'Emo Wholebrain' } -0.014776 0.0067931 -2.1752 0.034573 -0.31074

Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83

Col 1: Pain Wholebrain Col 2: Cog Wholebrain Col 3: Emo Wholebrain --------------------------------------------- Tests of column means against zero --------------------------------------------- Name Mean_Value Std_Error T P Cohens_d ___________________ __________ _________ _______ ________ ________ {'Pain Wholebrain'} 0.0058523 0.0074284 0.78783 0.43467 0.11255 {'Cog Wholebrain' } 0.011929 0.0052882 2.2559 0.028674 0.32226 {'Emo Wholebrain' } -0.016598 0.0067041 -2.4757 0.016877 -0.35367

Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii Direct calls to spm_defauts are deprecated. Please use spm('Defaults',modality) or spm_get_defaults instead. loading mask. mapping volumes. checking that dimensions and voxel sizes of volumes are the same. Pre-allocating data array. Needed: 19568052 bytes Loading image number: 49 Elapsed time is 2.467552 seconds. Image names entered, but fullpath attribute is empty. Getting path info. Number of unique values in dataset: 4760143 Bit rate: 22.18 bits

SPM12: spm_check_registration (v7759) 12:32:54 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 Grouping contiguous voxels: 1 regions

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 3 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 14.29% Expected 2.45 outside 95% ellipsoid, found 4 Potential outliers based on mahalanobis distance: Bonferroni corrected: 3 images Cases 27 28 44 Uncorrected: 4 images Cases 27 28 33 44 Retained 10 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 48.98% Expected 2.45 outside 95% ellipsoid, found 2 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 2 images Cases 28 45 Mahalanobis (cov and corr, q<0.05 corrected): 3 images Outlier_count Percentage _____________ __________ global_mean 1 2.0408 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 3 6.1224 mahal_cov_uncor 4 8.1633 mahal_cov_corrected 3 6.1224 mahal_corr_uncor 2 4.0816 mahal_corr_corrected 0 0 Overall_uncorrected 5 10.204 Overall_corrected 3 6.1224

SPM12: spm_check_registration (v7759) 12:33:15 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 Grouping contiguous voxels: 1 regions Grouping contiguous voxels: 1 regions Grouping contiguous voxels: 1 regions

current length is 49

after removing 3 participants, size is now 46

"participants that are outliers:... sub-0085" "participants that are outliers:... sub-0086" "participants that are outliers:... sub-0123"

{'sub-0085'} {'sub-0086'} {'sub-0123'}

One-sample t-test Calculating t-statistics and p-values

SPM12: spm_check_registration (v7759) 12:33:19 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Image 1 FDR q < 0.050 threshold is 0.004538 Image 1 92 contig. clusters, sizes 1 to 1720 Positive effect: 2559 voxels, min p-value: 0.00000024 Negative effect: 6503 voxels, min p-value: 0.00000000

SPM12: spm_check_registration (v7759) 12:33:21 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Setting up fmridisplay objects sagittal montage: 92 voxels displayed, 8970 not displayed on these slices sagittal montage: 64 voxels displayed, 8998 not displayed on these slices sagittal montage: 85 voxels displayed, 8977 not displayed on these slices axial montage: 1569 voxels displayed, 7493 not displayed on these slices axial montage: 1789 voxels displayed, 7273 not displayed on these slices

Input image 1 fullpath_was_empty _____________________________________________________________________ testr_low words_low testr_high words_high _________ ____________ __________ _____________ -0.35924 {'motion' } 0.25581 {'verb' } -0.33581 {'visual' } 0.2522 {'verbal' } -0.29026 {'spatial' } 0.19788 {'reward' } -0.2658 {'shape' } 0.19185 {'word' } -0.26427 {'object' } 0.18849 {'retrieval'} -0.26314 {'objects' } 0.17788 {'demand' } -0.24786 {'tactile' } 0.17371 {'memory' } -0.23855 {'hand' } 0.17319 {'affect' } -0.23096 {'eye' } 0.1723 {'sentences'} -0.22553 {'position'} 0.1707 {'correct' }

Loaded images: /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Negative_Emotion.nii

Table of correlations Group:1 -------------------------------------- T-test on Fisher's r to Z transformed point-biserial correlations R_avg T P sig Pain Wholebrain 0.0009 0.1254 0.9007 0.0000 Cog Wholebrain -0.0037 -0.8233 0.4144 0.0000 Emo Wholebrain 0.0025 0.2935 0.7704 0.0000

Col 1: Pain Wholebrain Col 2: Cog Wholebrain Col 3: Emo Wholebrain --------------------------------------------- Tests of column means against zero --------------------------------------------- Name Mean_Value Std_Error T P Cohens_d ___________________ __________ _________ ________ _______ ________ {'Pain Wholebrain'} 0.00092883 0.0074427 0.1248 0.9012 0.017828 {'Cog Wholebrain' } -0.0037473 0.0045527 -0.82309 0.41453 -0.11758 {'Emo Wholebrain' } 0.0024771 0.0083846 0.29543 0.76894 0.042205

Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83

Col 1: Pain Wholebrain Col 2: Cog Wholebrain Col 3: Emo Wholebrain --------------------------------------------- Tests of column means against zero --------------------------------------------- Name Mean_Value Std_Error T P Cohens_d ___________________ __________ _________ ________ _______ ________ {'Pain Wholebrain'} 0.00067579 0.0073155 0.092378 0.92678 0.013197 {'Cog Wholebrain' } -0.0036726 0.004103 -0.89511 0.37519 -0.12787 {'Emo Wholebrain' } 0.0027361 0.0081653 0.33509 0.73902 0.04787

Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii Direct calls to spm_defauts are deprecated. Please use spm('Defaults',modality) or spm_get_defaults instead. loading mask. mapping volumes. checking that dimensions and voxel sizes of volumes are the same. Pre-allocating data array. Needed: 19568052 bytes Loading image number: 49 Elapsed time is 2.797185 seconds. Image names entered, but fullpath attribute is empty. Getting path info. Number of unique values in dataset: 4759989 Bit rate: 22.18 bits

SPM12: spm_check_registration (v7759) 12:34:02 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 Grouping contiguous voxels: 1 regions

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 3 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 16.33% Expected 2.45 outside 95% ellipsoid, found 3 Potential outliers based on mahalanobis distance: Bonferroni corrected: 3 images Cases 27 43 44 Uncorrected: 3 images Cases 27 43 44 Retained 8 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 53.06% Expected 2.45 outside 95% ellipsoid, found 0 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 0 images Cases Mahalanobis (cov and corr, q<0.05 corrected): 3 images Outlier_count Percentage _____________ __________ global_mean 2 4.0816 global_mean_to_variance 1 2.0408 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 2 4.0816 mahal_cov_uncor 3 6.1224 mahal_cov_corrected 3 6.1224 mahal_corr_uncor 0 0 mahal_corr_corrected 0 0 Overall_uncorrected 3 6.1224 Overall_corrected 3 6.1224

SPM12: spm_check_registration (v7759) 12:34:24 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 Grouping contiguous voxels: 1 regions Grouping contiguous voxels: 1 regions Grouping contiguous voxels: 1 regions

current length is 49

after removing 3 participants, size is now 46

"participants that are outliers:... sub-0085" "participants that are outliers:... sub-0120" "participants that are outliers:... sub-0123"

{'sub-0085'} {'sub-0120'} {'sub-0123'}

One-sample t-test Calculating t-statistics and p-values

SPM12: spm_check_registration (v7759) 12:34:28 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Image 1 FDR q < 0.050 threshold is 0.005935 Image 1 115 contig. clusters, sizes 1 to 1769 Positive effect: 4754 voxels, min p-value: 0.00000000 Negative effect: 7096 voxels, min p-value: 0.00000000

SPM12: spm_check_registration (v7759) 12:34:30 - 09/06/2023 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Setting up fmridisplay objects sagittal montage: 346 voxels displayed, 11504 not displayed on these slices sagittal montage: 338 voxels displayed, 11512 not displayed on these slices sagittal montage: 359 voxels displayed, 11491 not displayed on these slices axial montage: 2195 voxels displayed, 9655 not displayed on these slices axial montage: 2489 voxels displayed, 9361 not displayed on these slices

Input image 1 fullpath_was_empty _____________________________________________________________________ testr_low words_low testr_high words_high _________ ___________________ __________ ________________ -0.32034 {'person' } 0.32774 {'visual' } -0.29939 {'trait' } 0.30119 {'eye' } -0.29672 {'default' } 0.26984 {'target' } -0.29473 {'social' } 0.26851 {'letter' } -0.28863 {'personal' } 0.26643 {'maintenance' } -0.28335 {'positive' } 0.26428 {'visuospatial'} -0.28266 {'self' } 0.25838 {'saccade' } -0.2764 {'negative' } 0.25678 {'working' } -0.2688 {'rating' } 0.24584 {'spatial' } -0.26411 {'selfreferential'} 0.24093 {'attention' }

Loaded images: /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Pain.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Cognitive_Control.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pMCC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_aMCC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_pACC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_sgACC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_vmPFC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_dMFC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_MFC_Negative_Emotion.nii /Users/h/Documents/MATLAB/Neuroimaging_Pattern_Masks/Multivariate_signature_patterns/2018_Kragel_MFC_Generalizability/bPLS_Wholebrain_Negative_Emotion.nii

Table of correlations Group:1 -------------------------------------- T-test on Fisher's r to Z transformed point-biserial correlations R_avg T P sig Pain Wholebrain 0.0024 0.3490 0.7286 0.0000 Cog Wholebrain -0.0295 -4.4242 0.0001 1.0000 Emo Wholebrain 0.0241 2.9398 0.0050 1.0000

Col 1: Pain Wholebrain Col 2: Cog Wholebrain Col 3: Emo Wholebrain --------------------------------------------- Tests of column means against zero --------------------------------------------- Name Mean_Value Std_Error T P Cohens_d ___________________ __________ _________ _______ __________ ________ {'Pain Wholebrain'} 0.0023727 0.0068003 0.3489 0.72869 0.049843 {'Cog Wholebrain' } -0.029451 0.0066553 -4.4252 5.5287e-05 -0.63217 {'Emo Wholebrain' } 0.024132 0.0082056 2.9409 0.0050239 0.42012

Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 Warning: Some images have zero values in some of the 411578 voxels in weight mask. These will be excluded from similarity analysis image-wise. Number of zero or NaN values within weight mask, by input image: 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83

Col 1: Pain Wholebrain Col 2: Cog Wholebrain Col 3: Emo Wholebrain --------------------------------------------- Tests of column means against zero --------------------------------------------- Name Mean_Value Std_Error T P Cohens_d ___________________ __________ _________ _______ __________ ________ {'Pain Wholebrain'} 0.0025075 0.0066541 0.37684 0.70795 0.053835 {'Cog Wholebrain' } -0.028171 0.0064598 -4.361 6.8231e-05 -0.623 {'Emo Wholebrain' } 0.023551 0.0081578 2.887 0.0058157 0.41242